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In the context of Pandas UDFs, explain the concept of lazy evaluation and its benefits when working with large datasets in Spark. Provide an example of how you would implement lazy evaluation in a Pandas UDF.
A
Lazy evaluation is a technique where the evaluation of an expression is deferred until its value is actually needed.
B
Lazy evaluation is a technique where the evaluation of an expression is performed immediately, but the result is cached for future use.
C
Lazy evaluation is a technique where the evaluation of an expression is performed in parallel across multiple nodes in a cluster.
D
Lazy evaluation is not applicable when working with Pandas UDFs in Spark.
